GTM AI Engineer

Customer.io

GTM AI Engineer responsible for scaling AI agents for Customer.io, enhancing communication systems. Collaborating with teams to ensure agent reliability and facilitate production-ready transitions.

Posted 7/10/2026full-timeRemote • Oregon • 🇺🇸 United StatesMid-LevelSenior💰 $140,000 - $170,000 per yearWebsite

Tech Stack

Tools & technologies

CloudGoogle Cloud PlatformKubernetes

About the role

Key responsibilities & impact

Alpha-to-production ownership — take newly built agents from working v1 to production-ready: write evals, harden prompts and tool definitions, and refactor prototype scaffolding into clean, production-quality code.
Observability & stability — instrument tracing, logging, and monitoring across the agent fleet so we catch regressions before our 120+ GTM users do.
Deployment & infrastructure — stand up and maintain the pipelines that get agents into users' hands without surprises, owning environment parity and release hygiene on our GCP stack.
Database administration — own how agents read from and write to our databases, safely and at scale.
Fleet maintenance — monitor agent behavior in production, triage issues, and ship the steady stream of improvements that make an agent indispensable rather than just useful.
Partner closely with the GTM AI team — free up our agent builders to stay in their zero-to-one wheelhouse while you own scale and reliability.
Bring an outside point of view — tell us what we built wrong, and back it up with a plan to fix it.

Requirements

What you’ll need

4+ years in software engineering, platform/infrastructure engineering, or a similarly technical role, ideally at a B2B SaaS company.
Comfort working in the terminal daily, with a real GitHub PR-and-deploy workflow.
Cloud hosting experience — Kubernetes, VMs, or equivalent; Google Cloud experience strongly preferred.
Experience with how agents interact with and edit databases, including some hands-on database administration.
Familiarity with LLM-based application development: prompt engineering, tool/function calling, evals, and modern agent frameworks.
Ability to prompt AI tools correctly, review their output critically, and direct them to QA their own work — this is an AI-native role, not a hand-coding one.
Scrappy enough to iterate fast, disciplined enough to think about consistency once something needs to scale.
A point of view, and the willingness to ask "why did you build it that way?"

Benefits

Comp & perks

100% coverage of medical, dental, vision, mental health, and supplemental insurance premiums for you and your family
16 weeks paid parental leave
Unlimited PTO
Stipends for remote work and wellness
A professional development budget

ATS Keywords

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Hard Skills & Tools

Software EngineeringDatabase AdministrationPrompt EngineeringTool/Function CallingEvalsAgent FrameworksKubernetesGoogle CloudMonitoringLogging

Soft Skills

Critical ReviewIterative ThinkingProblem-SolvingCollaborationCommunication